factor.model function

Find R = F F' + U2 is the basic factor model

The basic factor or principal components model is that a correlation or covariance matrix may be reproduced by the product of a factor loading matrix times its transpose. Find this reproduced matrix. Used by factor.fit, VSS, ICLUST, etc.

factor.model(f,Phi=NULL,U2=TRUE)

Arguments

• f: A matrix of loadings.
• Phi: A matrix of factor correlations
• U2: Should the diagonal be model by ff' (U2 = TRUE) or replaced with 1's (U2 = FALSE)

Returns

A correlation or covariance matrix.

References

Gorsuch, Richard, (1983) Factor Analysis. Lawrence Erlebaum Associates.

Revelle, W. In preparation) An Introduction to Psychometric Theory with applications in R (https://personality-project.org/r/book/)

Author(s)

revelle@northwestern.edu

https://personality-project.org/revelle.html

See Also

ICLUST.graph,ICLUST.cluster, cluster.fit, VSS, omega

Examples

f2 <- matrix(c(.9,.8,.7,rep(0,6),.6,.7,.8),ncol=2)
mod <- factor.model(f2)
round(mod,2)